OCB đang tuyển dụng Senior Data Engineer/ Data Architect (Retail Banking Digital Transformation) — vị trí làm việc tại Hồ Chí Minh.
Thông tin tuyển dụng OCB
| Thông tin | Chi tiết |
|---|---|
| Vị trí | Senior Data Engineer/ Data Architect (Retail Banking Digital Transformation) |
| Ngân hàng | OCB |
| Đơn vị | Dữ liệu và phân tích |
| Địa điểm | Hồ Chí Minh |
| Mức lương | Thỏa thuận |
| Hạn nộp hồ sơ | 2026-08-31 |
Mô tả công việc
-
Bachelor’s degree in Computer Science, Data Science, Information Systems, Software Engineering, or equivalent practical experience.
-
Strong background in Data Architecture, Data Engineering, Data Warehouse, or enterprise-scale data platforms.
-
Strong understanding of Data Architecture principles, Enterprise Data Architecture, Data Integration Architecture, and modern data platform architectures.
-
Strong knowledge of Data Warehouse, Data Lake, Lakehouse, Data Mart, Operational Data Store, and database design principles.
-
Strong hands-on experience in data modeling, including Conceptual Data Model, Logical Data Model, and Physical Data Model.
-
Solid understanding of dimensional modeling, normalized data models (3NF), and enterprise data modeling techniques.
-
Hands-on experience with Databricks (Cloud-based) or Oracle Data Warehouse environments for designing enterprise data solutions (mandatory requirement).
-
Experience in relational databases and data platforms, including Oracle, SQL Server, MySQL, and DB2 (DB2 is highly preferred).
-
Strong understanding of data integration patterns, including Batch, CDC, API-based integration, Event-driven, Near Real-time, and Streaming.
-
Experience in designing end-to-end data flows from source systems through ingestion, storage, transformation, and consumption layers.
-
Experience with Cloud platforms (AWS / Azure / GCP) and cloud-based data architectures.
-
Ability to translate business requirements and business capabilities into scalable data architecture and data models.
-
Ability to review technical designs, identify architectural risks and trade-offs, and provide clear recommendations.
-
Strong analytical thinking, structured problem-solving, and ability to work with complex enterprise environments.
-
Strong communication and stakeholder management skills, with the ability to collaborate across business, architecture, engineering, infrastructure, and vendor teams.
-
Experience with Agile Software Development and a solid understanding of Agile principles, Scrum methodology, and collaborative delivery models.
-
Team player with a proactive attitude and willingness to continuously learn and self-develop.
Nice to Have (Strong Plus):
-
Experience or knowledge of IBM Banking Data Model or other enterprise banking data models.
-
Experience with Data Vault 2.0, including Raw Vault, Business Vault, PIT, and Bridge structures.
-
Experience with Databricks Lakehouse Architecture, Unity Catalog, and Medallion Architecture.
-
Understanding of banking data domains such as Customer, Account, Product, Transaction, Finance, Risk, and Regulatory Reporting.
-
Experience with Data Governance concepts and tools, including Business Glossary, Metadata Management, Data Lineage, Data Quality, and Data Ownership.
-
Understanding of DataOps practices, including CI/CD, automated testing, monitoring, logging, and data quality automation.
-
Experience with Enterprise Architecture frameworks or methodologies such as TOGAF.
-
Experience working with large-scale data transformation or legacy Data Warehouse modernization programs.
Yêu cầu ứng viên
-
Bachelor’s degree in Computer Science, Data Science, Information Systems, Software Engineering, or equivalent practical experience.
-
Strong background in Data Architecture, Data Engineering, Data Warehouse, or enterprise-scale data platforms.
-
Strong understanding of Data Architecture principles, Enterprise Data Architecture, Data Integration Architecture, and modern data platform architectures.
-
Strong knowledge of Data Warehouse, Data Lake, Lakehouse, Data Mart, Operational Data Store, and database design principles.
-
Strong hands-on experience in data modeling, including Conceptual Data Model, Logical Data Model, and Physical Data Model.
-
Solid understanding of dimensional modeling, normalized data models (3NF), and enterprise data modeling techniques.
-
Hands-on experience with Databricks (Cloud-based) or Oracle Data Warehouse environments for designing enterprise data solutions (mandatory requirement).
-
Experience in relational databases and data platforms, including Oracle, SQL Server, MySQL, and DB2 (DB2 is highly preferred).
-
Strong understanding of data integration patterns, including Batch, CDC, API-based integration, Event-driven, Near Real-time, and Streaming.
-
Experience in designing end-to-end data flows from source systems through ingestion, storage, transformation, and consumption layers.
-
Experience with Cloud platforms (AWS / Azure / GCP) and cloud-based data architectures.
-
Ability to translate business requirements and business capabilities into scalable data architecture and data models.
-
Ability to review technical designs, identify architectural risks and trade-offs, and provide clear recommendations.
-
Strong analytical thinking, structured problem-solving, and ability to work with complex enterprise environments.
-
Strong communication and stakeholder management skills, with the ability to collaborate across business, architecture, engineering, infrastructure, and vendor teams.
-
Experience with Agile Software Development and a solid understanding of Agile principles, Scrum methodology, and collaborative delivery models.
-
Team player with a proactive attitude and willingness to continuously learn and self-develop.
Nice to Have (Strong Plus):
-
Experience or knowledge of IBM Banking Data Model or other enterprise banking data models.
-
Experience with Data Vault 2.0, including Raw Vault, Business Vault, PIT, and Bridge structures.
-
Experience with Databricks Lakehouse Architecture, Unity Catalog, and Medallion Architecture.
-
Understanding of banking data domains such as Customer, Account, Product, Transaction, Finance, Risk, and Regulatory Reporting.
-
Experience with Data Governance concepts and tools, including Business Glossary, Metadata Management, Data Lineage, Data Quality, and Data Ownership.
-
Understanding of DataOps practices, including CI/CD, automated testing, monitoring, logging, and data quality automation.
-
Experience with Enterprise Architecture frameworks or methodologies such as TOGAF.
-
Experience working with large-scale data transformation or legacy Data Warehouse modernization programs.
Cách thức ứng tuyển
Xem chi tiết và ứng tuyển tại: OCB
Ngày đăng: 15/07/2026
Nguồn: OCB
Đăng bởi: UB Job Crawler